INCORPORATION OF WEIBULL DISTRIBUTION IN L-MOMENTS METHOD FOR
INCORPORATION OF WEIBULL DISTRIBUTION IN L-MOMENTS METHOD FOR
复制标题
将威布尔分布纳入 L 矩方法中
DOI：
10.9753/icce.v32.waves.62
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
H. Kawai
中科院分区：
文献类型：
--
作者：
Y. Goda;M. Kudaka;H. Kawai
本文导出了威布尔分布的L矩，并将其应用于日本海东岸沿着11个测站的超阈波高区域频率分析。波浪测量的有效持续时间从18.0年到37.2年不等，平均每年发生10.4到15.1起事件。11个观测站被分为三个区域，以确保数据的均匀性。威布尔分布和广义帕累托（GPA）分布都很好地拟合观测数据。100年波高变化从8.2到11.2米的威布尔和7.6至10.3米的GPA。GPA分布不推荐用于确定这些台站的设计波，因为它具有固有的上限和预测不足的趋势。
引用
Coles，S. 2001.极端值的统计建模介绍，Springer，208 p。
Goda，Y.，Konagaya，O.，Takeshita，N.，Hitomi，H.，和T.永井2000.通过区域分析估算的极端波高的人口分布，海岸工程2000（第26届ICCE会议，悉尼），ASCE，悉尼，1078-1091。
Greenwood，J A.，J. M. Landwehr，N. C. Matalas和J.R.沃利斯。1978.概率加权矩：定义和与几种分布参数的关系，可以用逆形式表示，水资源研究，Vol. 15，No. 5，pp. 1049-1064.
http://dx.doi.org/10.1029/WR015i005p01049
霍斯金M. 1990. L-moments：Analysis and Estimation of Distributions Using Linear Combinations of Order Statistics，J. Roy.统计学会，Series B，52，pp. 105-24.
霍斯金M.和J.R.沃利斯。1997.区域频率分析，剑桥大学出版社，224页。
http://dx.doi.org/10.1017/CBO9780511529443
马，问。-美国，李，Y. B.，和J. Li，2006年。基于L-矩的显著波高区域频率分析，中国海洋工程，20（1），pp. 85-98.
彼得鲁阿斯卡斯角和P.M.。阿加德1971.用于估算设计波高的历史风暴数据外推，J. Soc.石油工程，第11页。23-27.
货车盖尔德A. J. M. 2000.土木结构基于风险设计的统计方法论文德尔夫特理工大学，249页。
货车盖尔德A. J.M.，J. De Ronde，N. W. Neykov，and P. Neytchev. 2000.极端波高的区域频率分析：以空间换取时间，海岸工程2000
The L-moments of the Weibull distribution are derived and incorporated in the regional frequency analysis of peaksover-threshold significant wave heights at eleven stations along the eastern coast of Japan Sea. The effective duration of wave measurements varies from 18.0 to 37.2 years with the mean rate of 10.4 to 15.1 events per year. The eleven stations are divided into three regions to assure homogeneity of the data. Both the Weibull and Generalized Pareto (GPA) distributions fit well to the observed data. The 100-year wave height varied from 8.2 to 11.2 m by the Weibull and 7.6 to 10.3 m by the GPA. The GPA distribution is not recommended for determination of design waves for these stations because it has an inherent upper limit and a tendency of under-prediction.
References
Coles, S. 2001. An Introduction to Statistical Modeling of Extreme Values, Springer, 208p.
Goda, Y., Konagaya, O., Takeshita, N., Hitomi, H., and T. Nagai. 2000. Population distribution of extreme wave heights estimated through regional analysis, Coastal Engineering 2000 (Proc. 26th ICCE, Sydney), ASCE, Sydney, 1078-1091.
Greenwood, J A., J. M. Landwehr, N. C. Matalas, and J. R. Wallis. 1978. Probability weighted moments: Definition and relation to parameters of several distributions expressable in inverse form, Water Resources Res., Vol. 15, No. 5, pp. 1049-1064.
http://dx.doi.org/10.1029/WR015i005p01049
Hosking, J. R. M. 1990. L-moments: Analysis and estimation of distributions using linear combinations of order statistics, J. Roy. Statistical Soc., Series B, 52, pp. 105-24.
Hosking, J. R. M. and J. R. Wallis. 1997. Regional Frequency Analysis, Cambridge Univ. Press, 224p.
http://dx.doi.org/10.1017/CBO9780511529443
Ma, Q.-S., Li, Y.-B., and J. Li .2006. Regional frequency analysis of siginicant wave heights based on L-moments, China Ocean Engineering, 20(1), pp. 85-98.
Petruaskas, C. and P. M. Aagaard. 1971. Extrapolation of historical storm data for estimating design wave heights, J. Soc. Petroleum Engrg., 11, pp. 23-27.
van Gelder, P. H. A. J. M. 2000. Statistical Methods for the Risk-Based Design of Civil Structures, Ph.D. thesis Delft University of Technology, 249p.
van Gelder, P. H. A. J. M., J. De Ronde, N. W. Neykov, and P. Neytchev. 2000. Regional frequency analysis of extreme wave heights: trading space for time, Coastal Engineering 2000